How to cite:
Abatzoglou, J.T., D.J. McEvoy, and K.T. Redmond, in press, The West Wide
Drought Tracker: Drought Monitoring
at Fine Spatial Scales, Bulletin of the American Meteorological
Society

Overview:

What is WestWide Drought Tracker?

The western United States consists of complex terrain where local
precipitation and temperature can vary dramatically across short
distances, which in turn impact local drought conditions. The
goal of WestWide Drought Tracker (WWDT) is to provide easy access to
fine-scale drought monitoring and climate products that can be utilized
by a variety of users. The climate data sets, drought indices,
and maps that are found on WWDT use monthly data which are updated with
new values at the beginning of each month using data from the PRISM
Climate Mapping Program.

What products are available on WWDT?

Drought Indices

Palmer Drought Severity Index (PDSI)

Self-Calibrated Palmer Drought Severity Index (sc-PDSI)

Palmer Z-Index

Standardized Precipitation Index (SPI)

Standardized Precipitation Evapotranspiration Index (SPEI)

Climate Data

Temperature Data and Anomaly (from 1981-2010 normals)

Temperature Percentiles

Precipitation Data and Anomaly (from 1981-2010 normals)

Precipitation Percentiles

Data Sources:

PRISM:

The PRISM Climate Mapping Program (Oregon State University) is an
ongoing effort to produce and disseminate the most detailed,
highest-quality spatial climate datasets currently available (Daly
et al., 1994). PRISM (Parameter-elevation Regressions on Independent
Slopes Model) is an analytical tool that uses point data, a digital
elevation model, and other spatial data sets to generate fine scale
(4-km, 2.5 arc-minutes) grid-based estimates of monthly precipitation
and temperature from 1895-present. PRISM uses point measurements of
climate data and a digital elevation model of terrain and is constantly
updated to map climate in the most difficult situations, including
high mountains, rain shadows, temperature inversions, coastal regions,
and associated complex meso-scale climate processes. We are currently
using the AN81m and AN81d datasets available from
http://www.prism.oregonstate.edu/

Drought Indices:

Palmer Drought Indices:

Palmer drought indices are based on a simplified water budget that
considers water supply (precipitation), demand (evapotranspiration) and
loss (runoff). Input data for these budget terms consist solely of
monthly temperature and precipitation. Fixed soil characteristics are
supplied independently by incorporating the available water holding
capacity of the top 250 cm of the soil acquired from the State Soil
Geographic Data Base (STATSGO). Snow and its effects are not
represented.

PDSI (Palmer Drought Severity Index) uses temperature
and precipitation data to determine the accumulated water excess or
deficit (Palmer, 1965). Values are referenced to the local climate so
that PDSI in different climates can be more readily compared. The
value of PDSI for a particular month is obtained from a weight applied
to the previous PDSI and an additional contribution from the present
month's Z-index (below).
http://drought.unl.edu/Planning/Monitoring/ComparisonofIndicesIntro/PDSI.aspx

sc-PDSI(self-calibrated PDSI) is a
locally calibrated version of the PDSI designed to make values of the
PDSI more comparable across space (Wells et al., 2004). The sc-PDSI
thus overcomes some of the limitations of the PDSI which were
originally calibrated using a few locations in the Midwestern USA. The
sc-PDSI ensures that values exceeding +4 occur 2 percent of the time,
and likewise for values less than -4. Note that the mean value of
sc-PDSI may not be 0 for a specific location and the sc-PDSI is not
intended to be a normalized version of the PDSI.

Palmer Z-Index: The Palmer Z Index measures short-term
drought on a monthly scale. The Z-value is also referenced to the
specific location and the climate for that time of year.

Standardized Precipitation Index:

The SPI (McKee et al., 1993) utilizes only monthly precipitation in its
calculation and was developed for two main reasons. First, water supply
in the form of precipitation is usually the most dominant component of
the soil's water budget, and strongly influences the Palmer
calculations. Secondly, a given location can be simultaneously in
short-term deficit, medium-term excess and long-term deficit. All forms
of the SPI pertain to some explicit time scale, which is part of the
name (e.g., 1-month SPI, 24-month SPI). The SPI is
"standardized" so that all precipitation climate regimes are
represented in common terms that can be compared with SPI from all
other locations, based on the historical probability distribution.
Monthly precipitation values are first added over the past N (N = 1, 2,
3...72) months. These are formed into a historical series, from which a
histogram or empirical distribution is formed. This is then approximated
by any of several possible theoretical distributions (the incomplete
beta distribution is used here). Various points on the distribution
(5th, 25th, 50th, 75th, 95th percentile, etc.) are then mapped onto a
normal (bell-shaped curve) distribution. The SPI is then taken as the
numerical value on a normal distribution of the departure from a long
term average. SPI has no units, and values can be thought of as
"like" standard deviations. Values exceeding +2 or -2 are
seen only about 5 percent of the time.
http://drought.unl.edu/Planning/Monitoring/ComparisonofIndicesIntro/SPI.aspx

Standardized Precipitation Evapotranspiration Index:

The SPEI utilizes monthly precipitation and average monthly temperature
in its calculation and was developed to help overcome some limitations
of the SPI (Vicente-Serrano et al., 2010). With the temperature
input potential evapotranspiration (PET) is calculated and a historical
time series of the simple water balance (precipitation – PET) is
used in place of the precipitation only time series used in the SPI.
The SPEI and SPI are calculated in a similar manner and both indices
have the advantage of being multi-scalar. The standardization procedure
for SPEI follows the same steps as SPI, however, the developers of SPEI
recommend using the three parameter log-logistic theoretical
distribution to account for common negative values which are found in
the time series (precipitation – PET). We use the entire period
of record for calculating SPI and SPEI, rather than just 1981-2010.
http://sac.csic.es/spei/index.html